The velocity of censorship: high-fidelity detection of microblog post deletions

  • Authors:
  • Tao Zhu;David Phipps;Adam Pridgen;Jedidiah R. Crandall;Dan S. Wallach

  • Affiliations:
  • Independent Researcher;Computer Science, Bowdoin College;Computer Science, Rice University;Computer Science, University of New Mexico;Computer Science, Rice University

  • Venue:
  • SEC'13 Proceedings of the 22nd USENIX conference on Security
  • Year:
  • 2013

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Abstract

Weibo and other popular Chinese microblogging sites are well known for exercising internal censorship, to comply with Chinese government requirements. This research seeks to quantify the mechanisms of this censorship: how fast and how comprehensively posts are deleted. Our analysis considered 2.38 million posts gathered over roughly two months in 2012, with our attention focused on repeatedly visiting "sensitive" users. This gives us a view of censorship events within minutes of their occurrence, albeit at a cost of our data no longer representing a random sample of the generalWeibo population. We also have a larger 470 million post sampling from Weibo's public timeline, taken over a longer time period, that is more representative of a random sample. We found that deletions happen most heavily in the first hour after a post has been submitted. Focusing on original posts, not reposts/retweets, we observed that nearly 30% of the total deletion events occur within 5- 30 minutes. Nearly 90% of the deletions happen within the first 24 hours. Leveraging our data, we also considered a variety of hypotheses about the mechanisms used by Weibo for censorship, such as the extent to which Weibo's censors use retrospective keyword-based censorship, and how repost/retweet popularity interacts with censorship. We also used natural language processing techniques to analyze which topics were more likely to be censored.